#### Overview of this book

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You’ll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you’ll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.
Preface
Free Chapter
Python Data Types and Structures
Introduction to Algorithm Design
Algorithm Design Techniques and Strategies
Stacks and Queues
Trees
Heaps and Priority Queues
Hash Tables
Graphs and Algorithms
Searching
Sorting
Selection Algorithms
String Matching Algorithms
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Index

# Implementation of quicksort

The main task of the quicksort algorithm is to first place the pivot element in its correct position so that we divide the given unsorted list into two sublists (left and right sublists); this process is called the partitioning step. The partitioning step is very important in understanding the implementation of the quicksort algorithm, so we will understand the implementation of the partitioning step first with an example. In this, given a list of elements, all the elements will be arranged in such a way that elements smaller than the pivot element will be on the left side of it, and elements greater than the pivot will be arranged to the right of the pivot element.

Let’s look at an example to understand the implementation. Consider the following list of integers. `[43, 3, 20, 89, 4, 77]`. We shall partition this list using the partition function:

`[43, 3, 20, 89, 4, 77]`

Consider the code of the partition function below; we will discuss...